Computerized classification method for significant coronary artery stenosis on whole-heart coronary MRA using 3D convolutional neural networks with attention mechanisms.

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Tác giả: Akiyoshi Hizukuri, Masaki Ishida, Ryohei Nakayama, Hajime Sakuma, Takuma Shiomi, Masafumi Takafuji

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: Japan : Radiological physics and technology , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 736710

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This study aims to develop a computerized classification method for significant coronary artery stenosis on whole-heart coronary magnetic resonance angiography (WHCMRA) images using a 3D convolutional neural network (3D-CNN) with attention mechanisms. The dataset included 951 segments from WHCMRA images of 75 patients who underwent both WHCMRA and invasive coronary angiography (ICA). Forty-two segments with significant stenosis (luminal diameter reduction

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